The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

The Data Science Lab Wasserstein Distance Using C# and Python Dr. James McCaffrey of Microsoft Research shows how to compute the Wasserstein distance and explains why it is often preferable to ...

The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, probability distributions often help solve problems that would otherwise be ...

People love sports for being unpredictable, but that doesn’t mean sports are actually unpredictable. It just means they feel that way. And no one knows this better than Bobby Skoff because Bobby Skoff ...

If you’re doing work in statistics, data science, or machine learning, the odds are high you’re using Python. And for good reason, too: The rich ecosystem of libraries and tooling, and the convenience ...